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Intro to Data Analysis

Utah Valley University - BIOL3100

Quick links:

Course Syllabus

Course file repository

Shared Course Notes

(Anyone with link can edit)

The philosophy of this course

R for Data Science Website

Collection of beginner R resources

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Table of Contents

Week 1 | Week 5 | Week 9 | Week 13

Week 2 | Week 6 | Week 10 | Week 14

Week 3 | Week 7 | Week 11 | Week 15

Week 4 | Week 8 | Week 12 | Week 16

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The Command Line, File Paths, Git

Week 1

Topics:

• Installing Software | Command-line | Git version control

Assignments

• Read: What is Git all about?
• Install Git, R, and R-Studio on your laptop (part of Assignment 1)
• Be ready to explain what Git, R, and R-Studio are.
• Do Assignment 1 and upload a link to your new GitHub account to Canvas.
• Take a look at this document to see where this class is going
• Go through ALL the resources below. I put them here for a reason. Most are short web resources or videos (some that I made).

Resources

• Recorded lesson video (Recorded during class and posted after)
• Video: Meet the command line of your computer
• Download Git
• Download R
• Download R-Studio
• Navigating with the command line (great video!)
• Git Cheat Sheet (handy reference)
• Git tutorial for beginners (another walkthrough, if you need it)
• Best Git Cheat Sheet Ever! (Excellent gift idea for a teacher…joking!)

Practice

• Make 10 more separate changes and commits to your README.md file and push each one to GitHub
• Close and open your command line terminal 10 times
• Open your command line terminal and navigate to your new personal GitHub repository for this course (Data_Course_LASTNAME) / Navigate back to your desktop / From your Desktop (without using “cd”) display the contents of Data_Course_LASTNAME/README.md onto your computer screen.
• Please view this short video clip from “Karate Kid” (Seriously)
  • When I tell you to close and open your command line 10 times, it’s not because I hate you.
  • It’s because I, too, have had to learn this stuff from scratch
  • It’s because I know that repetition is crucial to learning this, especially at the beginning
  • And it’s because if you don’t spend the time to do this stuff over and over now, by week 6 you will be drowning and helpless.
  • When I say “push 10 separate commits to your GitHub repo,” what I’m actually saying is “Show me ‘Paint the Fence’!”
  • Because very soon, Mr. Miyagi will be attacking you with things like “Error in url[i] = paste(df[,2], gsub(” “,”_“, : object of type ‘closure’ is not subsettable”

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Week 2

Topics

• File paths | Pipes | Redirection | Wildcards | Essential Unix Commands | Parameters

Assignments

• Assignment 2

Resources

• Recorded lesson video (Recorded during class and posted after)
• Remedial Unix Shell
• Basic Unix Commands
• Very Useful Tutorial
• On the Value of Command-Line Bullshittery
• On the Annoyance of Command-Line Bullshittery
• So is this stuff even useful for bioinformatics? YES!
• Video walkthroughs of some command line stuff:
  • Part 1 - first commands
  • Part 2 - pipes and wildcards
  • Part 3 - relative filepaths
  • Command line program flags/parameters
  • How to avoid two potentially dangerous command line errors
  • For-loops video walkthrough in BASH
• Bonus tips:
  • BASH aliases video
  • BASH alias examples

Practice

• Exercise 1
• Exercise 2
• Shell find exercise
• Pick some random files in our Data/ directory and practice (a bunch of times) using the following commands (with various flags and linking them with pipes):
  • head
  • tail
  • wc
  • ls
  • sort
  • uniq
• Practice using wildcards (*) to show the contents of random files
  • Pick a few random files in a directory and try to write a wildcard expression that shows ONLY those files (wash, rinse, repeat)
• find out what the following shell commands do and how to use them (then practice using them):
  • cp
  • mv

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Getting to Know R

Week 3

Topics

• R Data types and conversions | Reading and Writing Files | Packages and Projects

Assignments

• Read this chapter on what a “package” is in R
• Read this chapter on R-Projects (We will ALWAYS work from within R-Projects from now on)
• Do Assignment 3
• Do Assignment 4

Resources

• Recorded lesson video (Recorded during class and posted after)
• Data Types in R
• For-Loops
• Reading data into R

Practice

• Vectors
• Factors
• Characters
• Regular Sequences
• Indexing
• Missing Values
• Loops in R

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Week 4

Topics

• Logical Operations | Subsetting | “Grammar of Graphics” ggplot Intro

Assignments

• Read through the materials in the Resources section below
• Assignment 5
• Exam 1

Resources

• Recorded lesson video (Recorded during class and posted after)
• Subsetting
• More Subsetting (It’s important!)
• Operators

Practice

• Logical Operations
• Find a new built-in data set in R. Use several methods to subset it over and over until you are an expert!
• Out-of-order Code

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Visualizing a Data Set

Week 5

Topics

• ggplot | patchwork | ggforce

Assignments

• Assignment 6
• Ugly plot contest!
• Prevent embarrassment… see how NOT to make a chart, except for the Ugly Plot Contest, of course, where you should try to upend good sense.

Resources

• Recorded lesson video (Recorded during class and posted after)
• ggplot Introduction
• More ggplot
• ggforce
• patchwork
• Extensive ggplot2 Tutorial
• How to plot anything in ggplot part 1 | part 2 (This is a GOOD thing to watch!)

Practice

• Out-of-order Plotting Code
• ggplot Examples
• ggplot Shiny App Lets you use GUI to see ggplot code.

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Clean and Transform Data

Week 6

Topics

• Tidy Data | dplyr verbs | tidyr verbs

Assignments

• Read this paper: Tidy Data
• Assignment 7

Resources

• Recorded lesson video (Recorded during class and posted after)
• Tidy Data Chapter
• Transforming Data Frames
• dplyr Verbs
• tidyr Verbs
• tidyverse Cheat Sheet

Practice

• BioLog Challenge
• Out-of-order Code
• Out-of-order Code2

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Week 7

Topics

• Data Wrangling | Joins | The Curse of Other Peoples’ Data

Assignments

• Read This Handout
• Read This Paper
• Create a validated Excel Spreadsheet for data collection for the experiment we design in class
• Exam 2

Resources

• Recorded lesson video (Recorded during class and posted after)
• Data Wrangling Chapter
• Wrangling Cheat Sheet
• Visual Explanations of Joins
• Janitor package on CRAN

Practice

• Download this spreadsheet. See if you figure out all the things wrong with it.
• Error Sleuth Practice
• Data Entry Case Study

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Getting More From R

Week 8

Topics

• Writing Functions | Conditional Execution | source()

Assignments - Watch this video from Jenny Bryan about debugging

Resources

• Recorded lesson video (Recorded during class and posted after)
• Functions
• Conditional Execution

Practice

• Write a function that returns the min, max, and mean of any set of real numbers
• Write a function that takes a data frame and returns a new data frame with one random column removed
• Write a function that takes a data frame… if there are more than 3 columns, your function should return the column names as-is; if there are 3 or fewer columns, your function should return the column names in reverse order.
• Write a useful function that you might want to use in the future (your choice)
• Put all of these functions into a new R script and save it in your main data course repository
• In a new empty R script, call your functions with source() and test them out

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Model Building and Testing

Week 9

Topics

• Building and Testing Models

Assignments

• Assignment 8

Resources

• Recorded lesson video (Recorded during class and posted after)
• Modeling Intro
• Model Basics
• Model Fitting

Practice

• Building Models Example
• Intro to Hypothesis Testing
• Cross-Validation and Logistic Regression

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Week 10

Topics

• More models | Statistical Tests

Assignments

Resources

• Recorded lesson video (Recorded during class and posted after)
• Linear Regression
• More Linear Regression
• Common Statistical Tests
• Mixed-effect Models
• Everything is a Regression _ Introduction to mixed effects models This is a VERY good paper.

Practice

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Communicating Your Results

Week 11

Topics

• R-Markdown | Reproducible Reports

Assignments

• Assignment 9

Resources

• Recorded lesson video (Recorded during class and posted after)
• Intro to R Markdown
• Markdown Live Preview Generator
• Expert-Level Markdown Project

Practice

• Using the resources above, generate a markdown document that analyzes the “iris” data set and push it to a new GitHub repository named Iris_Markdown
• Play with options and code to create a document that looks good and presents your analysis and results clearly
• This is similar to Assignment_9, but I’m asking for a brand new “Iris_Markdown” repository that is self-contained.

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Week 12

Topics

• Proper Project Organization | Collaboration

Assignments

• Peer evaluation of Assignment 9 (Organization, Portability, Accuracy, Understandablity)
• Exam 3

Resources

• Recorded lesson video (Recorded during class and posted after)
• Project-oriented Workflows
• Reproducible, Portable, Self-Contained
• Proper Project Organization Example
• Another, More Detailed Example
• Project organization part 1 video
• Project organization part 2 video

Practice

• Peer evaluations of Iris_Markdown repositories (from last week); Clean them up and make them more organized

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Putting it all together

Week 13

Topics

• Data Analysis from raw to report

Assignments

• We will work together in class to do a complete analysis in real-time

Resources

• Recorded lesson video (Recorded during class and posted after)
• Benefits of Live Coding

Practice

• Analyze the “esoph” data set and generate a markdown report

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Week 14

Topics

• Building a website with GitHub and R-Markdown

Assignments

• Work on Final Project
• Create a GitHub Personal Website
• Upload a brief CV and the updated (improved) html of Assignment 9 to your new website

Resources

• Recorded lesson video (Recorded during class and posted after)
• GitHub Pages
• Here’s the GitHub repository for this course website
• Rmarkdown to web page walkthrough video
• Reproducible workflow video

Practice

• Go through my course website repository (link above) and try to relate the code there to the html version of the website your internet browser is displays

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Week 15

Topics

• TBD

Assignments

• Work on Final Project

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Week 16

Topics

• TBD

Assignments

• Exam 4 (Redo any previous exam to replace it’s score)

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‘Luck is statistics taken personally.’ – Penn Jillette